a hybrid meta-heuristic algorithm based on abc and firefly algorithms

abstract— in this paper we have tried to develop an altered version of the artificial bee colony algorithm which is inspired from and combined with the meta-heuristic algorithm of firefly. in this method, we have tried to change the main equation of searching within the original abc algorithm. on this basis, a new combined equation was used for steps of employed bees and onlooker bees. for this purpose, we had to define several new parameters for improving the quality of the proposed method. in this regard, we have introduced two new parameters to the method. the new method has been simulated within the software of matlab and it has also been run according to objective functions of sphere, griewank and ackley. all these functions are standard evaluation functions that are generally used for meta-heuristic algorithms. results that were yielded by the proposed method were better than the results of the initial algorithm and especially by increasing the number of variables of the problem, this improvement becomes even more significant. we have successfully established a better balance between concepts of exploration and exploitation, especially with increasing the repetition cycles, we have successfully controlled the concept of utilization with random parameters. tests have been ran more than 500 times.